Generative Artificial Intelligence (AI) Education Policies of UK Universities

Generative artificial intelligence (AI) technologies are becoming integral to academic and professional landscapes, with universities rapidly developing policies that govern ethical and effective usage. Yet such efforts are fragmented across institutions, from outright blanket bans to bespoke frameworks supporting AI application. Seeking to offer evidence of this fragmented approach, this study conducts a systematic content analysis of AI policies of UK Russell Group universities, with specific focus on learning and teaching. The analysis reveals differences in policy comprehensiveness, enforcement mechanisms, and educational initiatives, demonstrating varied institutional priorities and approaches. This includes widespread methods of integrating the technology within the learning experience or academic integrity governance strategies. Findings also indicate that while some universities have robust frameworks promoting AI literacy and ethical usage, others provide minimal guidelines, reflecting disparate levels of readiness and commitment to integrating AI into the curriculum. This study underscores the importance of clear, comprehensive policies in fostering equal access and ethical use of AI among students whilst supporting AI literacy. Recommendations include adopting uniform policy elements across institutions to standardise AI usage norms and enhance student preparedness for an AI-driven future. This research contributes to the discourse on educational policy development, emphasising the need for adaptive and forward-thinking strategies in higher education to address AI learning requirements.

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Publication Details

Journal
Enhancing Teaching and Learning in Higher Education
Published
2024-11-12
DOI
https://doi.org/10.62512/etlhe.20
Citations
10
Primary Topic
Engineering Education and Technology
Type
article
Field-Weighted Citation Impact
7.79
Controls
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article

Generative Artificial Intelligence (AI) Education Policies of UK Universities

Aarron Atkinson-Toal, Chuanbin Guo
10 citations
Enhancing Teaching and Learning in Higher Education
Engineering Education and Technology
7.79
article

Generative Artificial Intelligence (AI) Education Policies of UK Universities

Aarron Atkinson-Toal, Chuanbin Guo
article en
10 citations

Abstract

Generative artificial intelligence (AI) technologies are becoming integral to academic and professional landscapes, with universities rapidly developing policies that govern ethical and effective usage. Yet such efforts are fragmented across institutions, from outright blanket bans to bespoke frameworks supporting AI application. Seeking to offer evidence of this fragmented approach, this study conducts a systematic content analysis of AI policies of UK Russell Group universities, with specific focus on learning and teaching. The analysis reveals differences in policy comprehensiveness, enforcement mechanisms, and educational initiatives, demonstrating varied institutional priorities and approaches. This includes widespread methods of integrating the technology within the learning experience or academic integrity governance strategies. Findings also indicate that while some universities have robust frameworks promoting AI literacy and ethical usage, others provide minimal guidelines, reflecting disparate levels of readiness and commitment to integrating AI into the curriculum. This study underscores the importance of clear, comprehensive policies in fostering equal access and ethical use of AI among students whilst supporting AI literacy. Recommendations include adopting uniform policy elements across institutions to standardise AI usage norms and enhance student preparedness for an AI-driven future. This research contributes to the discourse on educational policy development, emphasising the need for adaptive and forward-thinking strategies in higher education to address AI learning requirements.

Enhancing Teaching and Learning in Higher EducationVol. 2
Durham University (GB)
Quality Education
Openalex Percentile: Top 3%
Engineering Education and Technology
7.79
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